Clears
Your backlog, delivered - from stories to reviewed pull requests
About Clears
Clears is a hosted platform that takes work from your backlog and carries it to a reviewed pull request without a person driving each step. It connects to Jira, to GitHub, Bitbucket or GitLab, and to Slack, then runs continuous background analysis over incoming tickets: root-causing the issue, scoping it, and assessing risk and feasibility, so that raw tickets become decisions that are either handled autonomously or escalated to the team when that is the right call.
The two claims worth examining are the Context Layer and the MCP surface. The Context Layer is described as memory shared with every agent on every run, which is aimed at the cold-start problem - an agent that re-reads the codebase from scratch on each ticket is both expensive and shallow. The MCP integration points the other way: rather than replacing the coding agent you already use, Clears exposes the whole board over MCP so your terminal agent can draw on its context, shape requirements, and dispatch tasks that then run, track and document themselves in the background, with any one of them pullable back to the terminal at any stage. Set against that, this is closed-source commercial software and every capability claim here comes from the vendor's own site. There is no public benchmark, no open trial artifact, and at the time of writing no reviews on its Product Hunt page; the social proof is four named engineering leaders at Windward, PlaxidityX, Sofwave and NoviSign. The launch itself was real - 373 upvotes and third place for the day on 17 August 2026 - but a strong launch is a signal about attention, not about whether the agent ships correct code.
You connect your ticket tracker and Git host, and Clears begins analysing the backlog in the background rather than waiting to be asked. Triage and intake run continuously: each ticket is root-caused, scoped and risk-assessed, and the platform then either executes it or escalates it to a human depending on what that assessment found.
Work that proceeds appears on a task board where every ticket is wired to its live agent session. You watch a requirement move to a merged pull request in one place, step in to steer when a session drifts, and parallelise across the backlog rather than running one agent at a time. The same board is reachable over MCP, so a coding agent in your terminal can command agents, processes, tickets and pull requests from a single prompt, and you can pull any task back into the terminal mid-flight with full control.
- •Autonomous Task Orchestration - Fleets of agents coordinated across your connected systems, presented as orchestrated and observable rather than as opaque background jobs
- •Context Layer - Shared memory available to every agent on every run, which the product positions as the thing that removes cold starts between tickets
- •Background Flows - Continuous deep analysis that root-causes, scopes and risk-assesses raw tickets, then decides between autonomous execution and escalation
- •Live Task Board - Every ticket bound to its agent session, so a requirement can be watched through to a merged pull request, steered mid-run, or resumed exactly where it stopped
- •MCP Surface - The board is exposed over MCP, so your existing terminal coding agent can use Clears for context and dispatch tasks into it
- •Standard Integrations - Jira, GitHub, Bitbucket, GitLab and Slack on the Pro plan
- •Enterprise Deployment - Custom workflows, large-scale codebase analysis, a dedicated customer engineer, priority support with SLA commitments, and deployment into your own VPC
Engineering organisations with a backlog larger than the team can work through, where the bottleneck is throughput on well-specified tickets rather than hard design work. The per-seat price makes it legible to a manager in a way that token billing is not, and the free trial requires no credit card, so the cost of finding out is low. Teams already standardised on Jira plus a mainstream Git host will have the least integration work.
Two groups should think twice. The Pro plan caps at 5 users, so any team past that size is in a sales conversation for Enterprise rather than self-serving. And if you prefer tools you can inspect, this is the closed-source, hosted end of the spectrum, with no open benchmark to check the claims against - the honest way to evaluate it is to run the trial on your own backlog and judge the pull requests, not to read the marketing.
